extfieldsofstudy: Medicine Biology

text:
The annotation and analysis of complex 3D plant organs using 3DCoordX

Abstract A fundamental question in biology concerns how molecular and cellular processes become integrated during morphogenesis. In plants, characterization of 3D digital representations of organs at single-cell resolution represents a promising approach to addressing this problem. A major challenge is to provide organ-centric spatial context to cells of an organ. We developed several general rules for the annotation of cell position and embodied them in 3DCoordX, a user-interactive computer toolbox implemented in the open-source software MorphoGraphX. 3DCoordX enables rapid spatial annotation of cells even in highly curved biological shapes. Using 3DCoordX, we analyzed cellular growth patterns in organs of several species. For example, the data indicated the presence of a basal cell proliferation zone in the ovule primordium of Arabidopsis (Arabidopsis thaliana). Proof-of-concept analyses suggested a preferential increase in cell length associated with neck elongation in the archegonium of Marchantia (Marchantia polymorpha) and variations in cell volume linked to central morphogenetic features of a trap of the carnivorous plant Utricularia (Utricularia gibba). Our work demonstrates the broad applicability of the developed strategies as they provide organ-centric spatial context to cellular features in plant organs of diverse shape complexity.

Introduction
It remains a salient challenge to understand the generation of biological shape. Gaining comprehensive insight into the multi-scale processes underlying morphogenesis critically depends on the quantitative description of molecular, cellular, and tissue-level parameters, such as gene and protein expression, cell geometry, and cell topology an organ-related frame of reference (Hejnowicz, 1984;Schmidt et al., 2014;Montenegro-Johnson et al., 2015;Strauss et al., 2021 (preprint)).
Realistic 3D digital organs with cellular resolution have become indispensable tools for the study of morphogenesis. They can be obtained by deep imaging of fluorescently marked specimens using for example confocal laser scanning microscopy or light sheet fluorescence microscopy followed by 3D cell segmentation of the obtained z-stacks of optical sections with the help of constantly improving software (Fernandez et al., 2010;Lowekamp et al., 2013;Barbier de Reuille et al., 2015;Stegmaier et al., 2016;Eschweiler et al., 2019;Wolny et al., 2020;Strauss et al., 2021 (preprint)). Tissues and organs of model plants are particularly well suited for the generation of such 3D digital representations. Plant cells are immobile simplifying the detection of cellular growth patterns associated with tissue formation. In addition, plant tissues are characterized by a small number of different cell types and often exhibit a well-structured, layered organization. Thus, they usually feature a cellular anatomy of manageable complexity. Accordingly, a growing number of realistic 3D digital tissues with cellular resolution are being generated, mainly in the model plant Arabidopsis (Arabidopsis thaliana; Bassel et al., 2014;Schmidt et al., 2014;Yoshida et al., 2014;Montenegro-Johnson et al., 2015Lora et al., 2017;Pasternak et al., 2017;Fridman et al., 2021;Graeff et al., 2021;Hernandez-Lagana et al., 2021;Refahi et al., 2021;Vijayan et al., 2021;Silveira et al., 2022).
With the help of 3D digital organs quantitative information about geometric and molecular parameters of up to thousands of cells can readily be obtained using opensource software, such as MorphoGraphX (Barbier de Reuille et al., 2015;Strauss et al., 2021 (preprint)). However, meaningful exploration of such complex data sets remains challenging. In particular, it is important to provide spatial context by placing the cell's data within an organ-related frame of reference (Hejnowicz, 1984). Several computational pipelines have been established that provide such a tissuelevel frame of reference and allow the semi-automatic annotation of 3D cellular properties in a plant tissue context with cellular resolution: iRoCS (Schmidt et al., 2014), 3DCellAtlas (Montenegro-Johnson et al., 2015), and 3DCellAtlas Meristem (Montenegro-Johnson et al., 2019). These computational pipelines have been applied very successfully for the annotation of cells and tissues in the main root and the hypocotyl, radially symmetric organs with limited curvature, or the shoot apical meristem (SAM), a dome-shaped structure exhibiting an anatomy of moderate complexity. However, not all plant organs fall into these simple morphogenetic categories. For example, strong curvature caused by developmentally regulated differential growth limits the usefulness of the implemented analytical strategies in iRoCS and 3DCellAtlas, particularly for indexing the axial position of a cell and determining its absolute distance to a reference. Yet, curvature represents a central element of the morphogenesis of plant organs with complex 3D shapes (Whitewoods and Coen, 2017). Many plant organs exhibit varying degrees of curvature, for example, the apical hook of seedlings, leaves, or floral organs, such as sepals or petals. The ovule, the major female reproductive organ in seed plants, constitutes a particularly prominent example. Ovules are characterized by complex anatomy consisting of a central "trunk," made up of several functionally distinct tissues stacked on top of each other, and by one or two laterally attached integuments, determinate planar tissues that eventually develop into the seed coat (Bouman, 1984). Moreover, most angiosperm ovules exhibit an extreme curvature due to asymmetric growth of the integuments (Endress, 2011).
Here, we developed generic strategies that allow the straightforward establishment of intrinsic coordinate systems in organs of simple or elaborate shape. We implemented those strategies in 3DCoordX, a module of MorphoGraphX. In 3DCoordX the annotation of cell position is guided by intrinsic, tissue-specific developmental axes. To work out the formal strategies we took advantage of a recently generated digital 3D reference atlas of ovule development in Arabidopsis . We illustrate how such a coordinate system enables rapid annotation of cell identity and cell position in 3D and greatly facilitates the quantitative analysis of cellular features. We applied our strategies to an investigation of cell proliferation patterns in the ovule primordium and the cellular basis of differential integument growth. Finally, we demonstrate the broad applicability of the introduced concepts by providing proof-of-concept analysis for selected parameters in different plant organs of varying shape complexity.

Curvature-related complications in the assignment of axial position
The analytical strategies for the positional annotation of individual cells relative to tissue organization depend on the structure under study. For example, the straightforward approaches employed in iRoCS and 3DCellAtlas involve cylinder coordinates and work very well for indexing axial position of cells relative to a reference in the root or hypocotyl, structures exhibiting limited curvature ( Figure 1A). However, asymmetric growth caused by differential cell proliferation and/or cell expansion can result in slanted or highly curved organs. In these instances, such approaches may lead to cells of the same indexed position having different absolute axial distances to a common reference ( Figure 1B). Thus, we devised a different strategy to minimize such axial distance errors when assigning 3D positional annotation to cells of organs that exhibit complex shapes. Our approach takes cues from central patterning events that frequently occur during early plant organogenesis, in particular the distinction of radial layers, the subdivision into anterior-posterior domains, and the establishment of a proximal-distal (axial) distance field (Figure 1, C and D). The proximal-distal distance of a cell relative to a user-defined reference is estimated by finding the shortest path through the cell centroids. Importantly, the search is confined to a given tissue layer and may not cross the anterior-posterior domain. The restriction to a tissue layer removes a large part of the axial distance error as the shortest path through the tissue layers cannot extend through interior tissues ( Figure 1C). On top of this restriction, prohibiting the shortest path from passing the anterior-posterior boundary further minimizes the error ( Figure 1D).

Developmental axes of the ovule
The need to assign spatial context to cellular features was sparked by our interest in the cellular basis of ovule development in Arabidopsis, an elaborately curved structure ( Figure 2A; Supplemental Figure S1; Supplemental Text S1). Moreover, in order to orient a 3D coordinate system along internal patterning processes our design of 3DCoordX was guided by intrinsic developmental axes of the developing ovule. Ovule development in Arabidopsis is well described (Robinson-Beers et al., 1992;Schneitz et al., 1995;Hernandez-Lagana et al., 2021;Vijayan et al., 2021;Supplemental Figure S1; staging according to Schneitz et al. (1995) and Vijayan et al. (2021). Here, we shortly summarize the different developmental axes that become apparent during its complex development ( Figure 2).
The ovule primordium exhibits the typical radial organization into the L1, L2, and L3 cell layers (Satina et al., 1940;Jenik and Irish, 2000; Figure 2A). In addition, the distal nucellus, central chalaza, and proximal funiculus represent three proximal-distal pattern elements along the trunk of the developing ovule. Gene expression patterns underlying the proximal-distal organization of the primordium are relatively well understood (Reiser et al., 1995;Gross-Hardt et al., 2002;Vijayan et al., 2021). The anterior-posterior axis is initially characterized by a primordial slant relative to the placenta surface, with the small angle of the slant facing the septum ( Figure 2B). The anterior-posterior axis persists in the main trunk in later stages as indicated by the organization of the embryo sac, the posterior initiation of the outer integument, the placement of the phloem in the funiculus, and the overall curvature . The anterior-posterior axis is further supported by differential expression of genes, such as the class III HD-ZIP gene PHABULOSA (Sieber et al., 2004) or the KANADI family member KAN1 (Supplemental Figure S2). The two integuments are characterized by their own intrinsic developmental axes (Figure 2, C-H). A distinct adaxial-abaxial (dorsoventral) axis is prominent as the individual cell layers of each integument differ in cellular morphology and gene expression patterns (Schneitz et al., 1995;Villanueva et al., 1999;Sieber et al., 2004;McAbee et al., 2006;Kelley et al., 2009; Figure 2C). Both integuments also feature their own proximal-distal axes ( Figure 2D; Supplemental Figure S1). Related to its hood-like shape the outer integument flanks a frontal section and features a medio-lateral axis (Figure 2, E and F). As a rule, we position the ovule with the anterior domain and the micropyle pointing to the left and the proximal end of the funiculus pointing toward the bottom right. Based on this arrangement we define the left and right lateral sides of the medio-lateral axis ( Figure 2H).
Primordium: cell layer detection, individual organ separation, and anterior-posterior domain annotation in 3D The annotation of cell position in 3D in the slanted ovule primordium required the application of the general principles outlined above. To be able to do so in a fast and robust manner we devised a method for radial tissue labeling. Current pipelines, such as 3DCellAtlas and 3DCellAtlas Dashed lines indicate shortest distances to the reference ignoring tissue layers. Solid lines mark the shortest distances to the reference that are restricted to tissue layers. Confining the shortest distance to a given layer reduces axial distance errors. The line at the bottom highlights the reference. The arrowhead marks origin cells. Origin cells exhibit a close distance in 3D to the reference (5-15 mm). D, 3D representation of (C) revealing how the anterior-posterior boundary further minimizes the axial distance error for a cell in the posterior half of the structure.
Meristem, invoke a surface mesh as a central tool for cell and tissue annotation in the root, hypocotyl, and the SAM (Montenegro-Johnson et al., 2015. However, establishing a surface mesh does not work well in situations where organs are in close contact with each other as is often the case for young ovule primordia attached to the placenta ( Figure 3A). The resulting individual surface meshes fail to outline the surfaces of the cells in contact and it is labor intensive to recreate a surface mesh in such instances.
To address this problem, we developed a strategy to perform automatic layer detection that groups cells into L1, L2, and L3 without a need for a surface mesh (Figure 3, A-D). In a first step L1, cells are clustered on the basis of a cell at the outer surface of the organ not being flanked by a neighboring cell at their outer surface. This feature is captured by defining the ratio of unshared wall area to shared wall area of individual cells (outside wall area ratio). Once L1 cells are clustered, L2 and L3 cells are found by their relative distances to the L1 cells. To this end, a network of cell centroids is established and the shortest number of centroids a cell must cross to reach to the nearest L1 cell is determined. The corresponding result essentially reveals how many cells separate the cell of interest from the L1. The information can be directly used to cluster cells into L2 and L3 as L2 cells are direct neighbors of L1 cells and L3 cells are separated from the L1 by more than one cell. The strategy does not  Schneitz et al. (1995) and Vijayan et al. (2021). B, 3D rendering of a placenta area carrying seven wild-type Stage 2-I ovules. The anterior-posterior and proximal-distal axes are marked. The sagittal, transverse, and frontal planes are marked by grids on the primordia. The frontal plane separates the anterior and posterior halves of the organ. The sagittal plane separates the left and right half of the organ. The dashed white arrow indicates the proximal-distal axis. Anterior and posterior side of the organ is highlighted with different colors in two of the representative ovules showing the sagittal and the frontal grid. Black dotted line indicates the placental surface to which the posterior side of the ovule is slanted with a small angle. C, Outer and inner integument tissues extracted from the 3D mesh for visualizing the abaxial-adaxial polarity. Tilted view of mid-sagittal sections through the outer and inner integument, respectively, of a Stage 3-IV 3D digital ovule. The arrows highlight the adaxial-abaxial axes of each integument. D-H, Visualization of different tissues in a Stage 2-V Arabidopsis ovules at different orientations of the organ. D, Posterior view of the ovule with the proximal-distal axis of the outer integument marked. E, Side view (left) and anterior view (right). Grid represents the frontal plane. The medio-lateral axis is indicated. F, Anterior view of the ovule visualizing the frontal region. The grid represents the mid-sagittal plane. G, A mid-sagittal section view of the ovule in (F) visualizing the maximal proximal-distal extension of the integuments. H, A 3D clipped view of the 3D digital ovule is displayed. It is oriented with the posterior side to the right. The 3D view allows the discrimination of the left-right sides of the 3D digital ovule. The dashed line indicates the medial line. an, anterior; ab, abaxial; ad, adaxial; ach, anterior chalaza; ch, chalaza; d, distal; ii, inner integument; es, embryo sac; fu, funiculus; l, lateral; le, left; m, medial; nu, nucellus; oi, outer integument; p, proximal; pch, posterior chalaza; po, posterior; ri, right. Scale bars: 20 mm.
completely solve the issue when surface cells of neighboring organs are in full contact. However, the process works well when there is partial contact that still leaves behind a substantial outside unshared cell wall area. This approach successfully annotated the radial tissue layers in ovule primordia of all stages. As examples, cell layer detection is shown for Stage 2-I ovule primordia (Figure 3, A-D) and the SAM (Supplemental Figure S3).
Another problem relates to the separation of the multiple ovule primordia attached to the placenta into distinct units to allow ovule-specific analyses. We devised a method that takes advantage of the cell connectivity graph (Figure 3, F-H). From a selected cell at the distal end on each different ovule, distances to all other cells on the cell connectivity graph are computed. Cells are then assigned a label based on their nearest selected cell on that graph. A further parameter sets a maximum size of the ovules (in number of cells from the selected cells) to separate the ovules from their surrounding tissue. To facilitate downstream analysis, different labeling types, such as the cell layers and the ovule labels, are combined to create a unique label for each layer in every ovule.
In the last step, cells of anterior and posterior domains of similar dimensions are obtained by manual selection (Figure 3, I and J). For the funiculus we also devised a semiautomatic method to distinguish the anterior and posterior domains (Supplemental Figure S4). In summary, the outlined approaches enable the generation of 3D digital ovule primordia of separate identities and near-perfect radial and anterior-posterior tissue annotation with minimal user input.

Primordium: assignment of proximal-distal position to individual cells in 3D
To determine the proximal-distal (axial) position of an ovule primordium cell we generated a method that applies to 3D digital ovules for which radial cell layers and the anterior-posterior domains have already been annotated. The proximal-distal position of each cell is calculated, either in terms of cell index or absolute or relative distance to a reference, in a two-step procedure ( Figure 3, K-N). In the first step, a Bezier ring (a mathematically defined curved line) will serve as reference for the proximal-distal distance field and is placed at one end of the tissue. In the case of the cone-shaped ovule primordium a small, near point-size Bezier ring is positioned at the distal tip of the primordium. Positioning the Bezier ring at the distal tip corresponds to a biologically relevant maximum of the phytohormone auxin at the tip as inferred from the expression of the auxin response reporter pDR5::GFP (Benková et al., 2003), the spatial signal of the auxin sensor R2D2 (ratiometric version of two DIIs; Liao et al., 2015;Kawamoto et al., 2020), and the finding that polar auxin transport mediated by PINFORMED1 is required for ovule primordium formation (Bencivenga et al., 2012;Galbiati et al., 2013). In case of the mature funiculus that is close in shape to a curved cylinder, a larger Bezier ring is placed at its proximal end. Origin cells are then defined by their close distance in 3D (usually 5-15 mm) to the user-specified Bezier ring (Figure 1, C and D). They act as seeds for the distance coordinates of the remaining cells of the tissue that are obtained by searching for the shortest path through the cell centroids to the centroid of an origin cell. The search is restricted to a radial layer and by the anterior-posterior boundary. It should be noted that with this approach small axial distance errors still occur within the anterior or posterior domains depending on the number of laterally arranged cell files within these areas. The remaining errors are typically in the range of a few microns, but can be eliminated when taking individual cell files into account. This is possible within the software, however, the procedure involves cumbersome manual annotation of all cell files for each cell layer. Moreover, the gain of resolution is minimal.

A coordinate system for integuments
We successfully applied to the integuments some of the same formal strategies as described for the primordium or funiculus. In an initial step, the integumentary adaxial-abaxial cell layers are labeled manually. In a subsequent step, medio-lateral coordinates of all cells of a given integument layer are established relative to a file of posterior midline cells ( Figure 4A). Cell distance is computed in terms of how many cells separate a given cell from the midline ( Figure 4B). Cells along the medio-lateral axis can be grouped further into median and lateral subdomains that occupy about half the width of an integument layer. For example, for the outer layer of the outer integument we grouped cells that are located three cells to the left or right of the posterior midline cells into the median domain. The remaining cells are classified as lateral cells ( Figure 4C). In the following step, proximal-distal distance coordinates are assigned for all integument cells. A Bezier ring is first placed at the proximal end of the inner side of the outer integument (next to its inner layer) facing the outer layer of the inner integument ( Figure 4D). The circular origin is in the same plane as the ring-shaped expression pattern of a reporter for CUP-SHAPED COTYLEDON3 (pCUC3::CFP) which marks the proximal base of the two innermost layers of the inner integument, respectively ( Figure 4E). Members of the CUC gene family are generally required for primordium initiation and organ boundary formation (Aida et al., 1997;Ishida et al., 2000;Takada et al., 2001;Breuil-Broyer et al., 2004;Sieber et al., 2007;Galbiati et al., 2013;Gonçalves et al., 2015). Origin cells are then defined by their close userspecified distance to the Bezier ring in 3D ($5-15 mm). As a direct result of the placement of the Bezier ring, cells of the outer layer of the outer integument that are in direct contact with the subepidermal proximal chalaza are assigned a negative value for the proximal-distal position (Figure 4, F and G). This feature can be used to separately cluster and analyze those cells. Finally, proximal-distal distance coordinates of the integument cells are obtained by searching for the shortest path through the cell centroids to the centroid of an origin cell (Figure 4, F-H). The search is again restricted to a given tissue layer and may not cross the medio-lateral boundary. Taken together, the procedure assigns medio-lateral and proximal-distal positions for all cells of the integuments.

Differential distribution of cellular growth patterns during early ovule development
To provide proof of concept for the usefulness of our computational tools in the quantitative analysis of cellular patterns in a 3D context we assessed spatial growth patterns in selected aspects of ovule development. To this end, we made use of a previously published dataset of wild-type 3D digital ovules of the Col-0 accession .
We first focused on primordium outgrowth. It was previously shown that ovule primordia grow in a continuous fashion based on an analysis of the total number of cells and the increase of organ volume from Stages 1-I to 2-I (Hernandez-Lagana et al., 2021;Vijayan et al., 2021). However, it remained unclear how cell numbers and cell volumes of the radial layers compare to each other. In addition, it was not known if mitoses are randomly distributed along the proximal-distal axis or if they preferentially occur in specific domains. To address these questions, we analyzed 53 3D digital wild-type ovule primordia that encompassed Stages 1-I to 2-I ( Figure 5, A and B).
We initially undertook a comparison of cell volumes between stages ( Figure 5C) and radial layers ( Figure 5D; Table 1). In this dataset, the L2-derived megaspore mother cells (MMCs) at Stage 2-I feature an average cell volume of 543.3 ± 120.6 mm 3 (mean ± SD) with a minimal volume of 335 mm 3 . Thus, the volume of the MMCs is beyond the largest cell volumes observed for other cells ( Figure 5C). We therefore eliminated the MMCs from this analysis to eliminate skewing of the results due to their out-of-range size. We observed that the average volume of L1 cells slightly increased during development while the average volume of L2/L3 cells stayed about constant ( Figure 5D; Table 1). The results further indicated that with the exception of the MMCs the L2 and L3 feature cells of about similar cell volumes while the L1 is composed of smaller cells.
We then compared cell numbers between stages ( Figure 5E) and radial layers ( Figure 5F; Table 1). Overall, we observed a steady increase in cell numbers during primordium outgrowth ( Figure 5E). The L1 covers a larger surface of the primordium than the L2 or L3. Considering this aspect and given the smaller cell volume of L1 cells in comparison to L2/L3 cells, we hypothesized that the L1 consists of more cells than the L2 and L3. This assumption was supported by layer-specific cell counts ( Figure 5F; Table 1). We also determined that the L1 showed the largest percentage increase in cell numbers, while the L3 showed the least percentage increase in cell numbers ( Figure 5G).
Next, we assessed the spatial distribution of mitoses. To this end we manually labeled cells that exhibit mitotic figures ( Figure 5, A and B) (see "Materials and methods"). In our dataset of 53 3D digital ovule primordial, we identified 26 specimens with at least one mitotic cell. Overall, we detected 52 mitotic cells distributed across those 26 specimens. We first asked if there were differences in the number of mitoses between the cell layers. We found 33 mitotic cells in the L1, 18 in the L2, and 1 in the L3. We also calculated the layer-specific fraction of cells in mitosis for Stages 1-I, 1-II, and 2-I (Table 1). For the L1 and L2, the values may point to differential dynamics in cell proliferation between the two layers during primordium formation. The determined mitotic index for the L3 is very likely an underestimate as the number of L3 cells and sampled ovules are small in this proof-of-concept analysis. We then investigated if there was a difference between the number of mitotic cells in the anterior and posterior L1. We found 23 and 10 mitoses in the anterior and posterior L1, respectively, indicating that more cell divisions occur in the anterior L1 domain. Finally, we took advantage of the 3DCoordX coordinates and analyzed the overall distribution of mitotic cells along the proximaldistal axis from Stages 1-I to 2-I. We found that $80%-85% of scored mitotic cells were located in the proximal half of the developing primordium ( Figure 5H).
Taken together, our data indicate that primordium outgrowth is preferentially driven by an increase in cell number, not cell volume. In addition, they suggest unequal spatial distribution of mitoses between cell layers and along the anterior-posterior and proximal-distal axes. A higher number of mitoses in the anterior domain might explain primordium slanting. The data further indicate that a cell proliferation zone located in the bottom half of the developing primordium contributes substantially to its outgrowth.
Funiculus curvature corresponds to differences in cell number and cell volume along the anterior-posterior and proximal-distal axes To obtain insight into the cellular processes underlying funiculus curvature, we performed an initial analysis of its cellular characteristics using 14 3D digital ovules of Stage 3-IV ( Figure 6, A-F). By this stage growth of the funiculus has ceased . We focused on the L1 and L2 layers. To investigate cellular features of the L2, we digitally removed the L1 from the 3D digital funiculi. First, we assessed the proximal-distal distance and cell number along the L1 midlines of the anterior and posterior domains, respectively ( Figure 6, A-F). We observed that the anterior midline was longer and characterized by a higher number of cells in comparison to the posterior midline. To directly compare volumes of anterior and posterior cells we converted the cells' coordinates into relative proximal-distal positions (Zhang et al., 2020). There we noticed a gradient in the volume of anterior L1 and L2 cells with the distalmost cells featuring nearly 1.5-2 times the volume of cells located at the proximal end ( Figure 6, E and F). We did not detect a noticeable volume increase in the posterior cells.
In summary, our data suggest that a combination of differential cell proliferation along the anterior-posterior axis and unequal cell growth along the proximal-distal axis of the anterior domain contributes to the curvature of the funiculus.

Proximal-distal growth gradient in Arabidopsis integuments
Genetic data indicated that asymmetric growth of the outer integument is instrumental for the anatropous shape of the ovule (Baker et al., 1997;Schneitz et al., 1997;Vijayan et al., 2021). However, the 3D architecture of integument cells in relation to their position within the tissue remained unknown. Thus, to provide proof of concept we undertook a first analysis of the 3D geometry of integument cells in 3D digital ovules of Stage 3-IV. We used 3DCoordX to measure cell volumes of the outer layer of the outer integument along the proximal-distal axis. We found a gradient in cell volume along this axis. We observed that proximal cells exhibited small cell volumes while, with the exception of small cells at the tip of the integument, distal cells were characterized by larger sizes ( Figure 7A). Next, we expanded the 3D cellular analysis to all cells of the integuments. In a typical Stage 3-IV 3D digital ovule, we found a proximal-distal gradient of cell volumes in cells of the other layers, but at a smaller scale compared to the outer layer of the outer integument (Figure 7, A-G). We then compared cell length to cell position along the proximal-distal axis in the medial   domain of the inner layer of the outer integument across five different specimens. We found that cell length increased along the proximal-distal axis ( Figure 7H). Taken together, our data suggest that preferential cell elongation along the proximal-distal axis may be an important factor underlying differential growth of the outer integument and ovule curvature.

Application to other plant organs
Finally, we explored if our approach for an organ-intrinsic coordinate system was useful beyond the Arabidopsis ovule and could be of value to provide spatial context to cellular growth patterns in different organs of various plant species. To this end, we investigated 3D digital plant organs of diverse morphological complexity. We first inspected the archegonium of the liverwort genetic model system Marchantia (Marchantia polymorpha). The archegonium is an organ of simple morphology consisting of two main tissues: the spherical venter harboring the egg cell and the elongated neck through which the sperm cell reaches the egg cell (Shimamura, 2016). We generated two 3D digital archegonia: a younger specimen A and an older specimen B. Both archegonia were imaged, 3D segmented, and cells of the neck, neck canal, venter, and venter canal were identified and labeled manually. We removed the egg and canal cells from our analysis and focused on the venters and the necks of the two 3D digital archegonia (Figure 8, A-F). A first inspection already revealed differences between the two specimens. We observed that the venter of specimen A possessed only one cell layer with no obvious signs of periclinal cell division. In contrast, we found that a scattered pattern of periclinal cell divisions had occurred in the venter of specimen B associated with the formation of a second cell layer (Figure 8, D and E;Shimamura, 2016). This observation indicated temporal and spatial asynchrony in the control of these periclinal cell divisions.
A monolayer of cells formed the necks of both specimens. We implemented an organ coordinate system to enable a spatial analysis of some basic cellular parameters along the long axes of the two specimens. We placed a Bezier ring at the boundary between the venter and neck cells (Figure 8, C and F). The placement of the ring resulted in the assignment of positive and negative organ coordinate values for the venter and neck cells, respectively. We then assessed the basis of the differences in neck lengths between the two specimens. Measuring neck length along the main central axis revealed that the neck of specimen B was about 2 times longer than specimen A (329 mm versus 160 mm). We then asked if the length disparity between the necks of the two specimens was due to a difference in cell numbers and/or cell elongation. We determined 98 and 114 neck cells for specimens A and B, respectively, indicating a minor difference in neck cell numbers. Next, we quantified cell length along the central organ axis for all neck cells. We observed that the neck cells of specimen A had an average length of 10.3 ± 2.4 mm and exhibited a relatively uniform cell length ( Figure 8G). Neck cells of specimen B showed a more heterogeneous distribution of cell length and were noticeably more elongated with an average cell length of 20.8 ± 5.6 mm. Moreover, cell elongation increased toward the tip of the neck in specimen B while no such increase was observed for specimen A ( Figure 8H). The results indicated that enhanced cell elongation along the central axis of the neck was mainly associated with the increase in neck length in specimen B in comparison to specimen A.
Finally, we turned our attention to a plant organ of complex 3D morphology. The cup-shaped trap of the aquatic carnivorous plant Utricularia (Utricularia gibba) represents a highly curved 3D leaf form (Reifenrath et al., 2006;Płachno et al., 2015). Quantitative growth analysis at the tissue level combined with computer modeling indicated that the complex shape transformations occurring during trap development are associated with differential rates and orientations of growth (Lee et al., 2019;Whitewoods et al., 2020). However, a quantitative analysis of 3D cellular parameters had not been performed. To obtain insight into the cellular basis of the growth patterns shaping the Utricularia trap we generated a 3D digital representation with cellular resolution of an intermediate-stage trap collected 6 d after initiation (Lee et al., 2019). By this stage, an invagination in the nearspherical young trap had occurred, followed by the formation of further folds and tissue broadening, and resulting in the emergence of the interior trap door and threshold (Figure 9, A-C). We manually labeled the various tissues, including the abaxial and adaxial cells of the wall, the threshold, and the combined trap door/palate domain, and distinguished between medial and lateral domains of the adaxial and abaxial wall, respectively. To define an origin of the distance coordinate system we placed an ellipsoid Bezier ring at the boundary between the base of the threshold and the wall of the trap ( Figure 9D). We then asked if there were position-related differences in cell volume in the epidermal layers of the wall and threshold by analyzing epidermal cells located along the respective midlines of the tissues (Figure 9, E-H). We observed that cell volume varied along the measured distances. For example, we noticed a sudden increase in cell volume in an interval from 240 to 320 mm for cells of the abaxial wall ( Figure 9G). This region precedes a prominent kink in the abaxial wall (Figure 9, E and F). In contrast, cell volumes of the adaxial wall dropped toward the end. The decrease in cell volume was likely associated with the tapering of the adaxial wall that could be observed in this area. Volumes of threshold cells positioned within a range of 80 mm to about 150 mm from the origin showed relatively small volumes in comparison to the cells flanking this interval ( Figure 9H). The 80-150 mm zone corresponded to a section of the threshold which was only moderately curved and provided a large surface exposed to the lumen of the trap (Figure 9, E and F). Taken together, the data revealed spatial differences in cell volume for all three examined tissues of this specimen and support the notion that differential cell growth contributes to the morphogenesis of the Utricularia trap.

Discussion
The generation of biological form can be explained in terms of growth oriented relative to an organ-centric coordinate system (Thompson, 1942;Coen and Rebocho, 2016;Whitewoods and Coen, 2017). To understand tissue morphogenesis, it is therefore essential to provide spatial context to the quantitative analysis of the molecular and cellular networks that underlie the development of tissues and organs. It requires robust methods that enable the objective assignment of position to individual cells in a rapid and reliable manner. Here, we developed 3DCoordX, a collection of computational tools that enable the assignment of organcentric coordinate systems to several different plant organs with complex shapes that were not accessible with previous methods. By applying mathematically defined criteria for the annotation of cell position in 3D the tools largely eliminate user-derived ambiguities in the cell annotation process. 3DCoordX is implemented as an add-on to the open-source software MorphoGraphX (Barbier de Reuille et al., 2015;Strauss et al., 2021 (preprint)). A detailed user guide can be found in the Supplement Text S2. 3DCoordX enables quantitative analyses of cellular features in their spatial context, in a rapid manner, and on a large scale.
We took advantage of the recently made available 3D digital reference atlas of the Arabidopsis ovule to develop generic conceptual and computational approaches that enable the assignment of 3D coordinate systems to organs of simple as well as complex curved morphology. Previous efforts, such as iRoCS (Schmidt et al., 2014) and 3DCellAtlas (Montenegro-Johnson et al., 2015), relied on externally imposed coordinate systems. The design of the strategies for the annotation of cell position presented here are guided by intrinsic patterning processes and assign cell distance in relation to organ-centric developmental axes. Such tissue polarity axes are thought to play a central role in the spatial control of growth (Kennaway et al., 2011;Kuhlemeier and Timmermans, 2016;Whitewoods and Coen, 2017). To accommodate the particular architecture of the ovule we devised two 3D coordinate systems, one for the main "trunk," the central proximal-distal axis consisting of the nucellus, chalaza, and funiculus, and one for the integuments. Both coordinate systems are based on similar general principles. First, we distinguish between individual cell layers as in the L1-L3 layers of the primordium or the adaxial-abaxial (dorso-ventral) cell layers of the two integuments. Importantly, with the concept of "outside wall area ratio" 3DCoordX embodies a strategy for the classification of the radial layers. It does not rely on a surface mesh for classification and thus is more versatile than other published methods. Second, the cell layers then become subdivided into two domains: the anterior-posterior domains of the trunk and the medio-lateral domains of the integument cell layers. Third, subsequent assignment of a proximal-distal distance value to each cell is constricted by these two prepatterns. For the placement of reference Bezier rings, we took cues from the localization of important developmental regulators, such as the presence of an auxin maximum at the distal tip of the ovule primordium or the CUC3 expression in the chalaza (Benková et al., 2003;Gonçalves et al., 2015;Liao et al., 2015;Kawamoto et al., 2020). As a result of the approach each cell is annotated in 3D with respect to the radial and proximal-distal dimensions as well as to either an anteriorposterior or medio-lateral axis. With the help of 3DCoordX, we readily discovered previously unidentified cellular growth patterns in the primordium and integuments. For example, our data indicate a basal cell proliferation zone in the ovule primordium and suggest that preferential cell proliferation in the anterior domain is important for primordium slanting. Moreover, we obtained evidence that the increase in cell volume along the proximal-distal axis of the outer integument, a tissue without radial symmetry, is mainly explained by an increase in cell length.
Importantly, our work revealed that the respective principles can be successfully applied to the establishment of coordinate systems for organs of varying degrees of morphological complexity and the subsequent quantitative analysis of 3D cellular parameters. We provided evidence for a preferential increase in cell length during axial neck growth of the Marchantia archegonium. Moreover, we identified distinct cellular patterns possibly associated with important morphological features of the intricately folded U. gibba trap. These data reveal that 3DCoordX has broad applicability and eliminates the need to work with multiple different pipelines when analyzing the cellular architecture of organs in 3D. The general strategies and computational methods put forward in this work will greatly reduce the time required for the spatial analysis of cellular parameters so central to various approaches, such as computational modeling of morphogenesis or comparative morphometry of specimens from different genotypes.

Clearing and staining of tissue samples
Treatment of ovules of the pKAN1::KAN1:2xGFP and the pCUC3::CFP lines was done as described in (Tofanelli et al., 2019) and . Tissue was fixed in 4% paraformaldehyde in PBS followed by two washes in PBS before transfer into the ClearSee solution (xylitol (10%, w/v), sodium deoxycholate (15%, w/v), urea (25%, w/v), in H 2 O; Kurihara et al., 2015). Clearing was done at least overnight or for up to 2-3 d. Cell wall staining with SR2200 (Renaissance Chemicals, Selby, UK) was performed as described in (Musielak et al., 2015). Cleared tissue was washed in PBS and then put into a PBS solution containing 0.1% SR2200 and a 1/1,000 dilution of the nuclear stain TO-PRO-3 iodide (Thermo Fisher Scientific Waltham, MA, USA) for 20 min. Tissue was washed in PBS for 1 min, transferred again to ClearSee for 20 min before mounting in Vectashield antifade agent (Vector Laboratories, Burlingame, CA, USA). Marchantia archegoniophores were fixed for 1 week in 4% paraformaldehyde in PBS followed by two washes in PBS before transfer to ClearSee. Clearing was done for 4-7 d. Cell wall staining and subsequent clearing, washing, and mounting steps were the same as for Arabidopsis ovules. Archegonia were dissected in Vectashield mounting medium (Vector Laboratories, Burlingame, CA, USA).

Microscopy and image acquisition
Confocal laser scanning microscopy of ovules stained with SR2200 and TO-PRO-3 iodide was performed on an upright Leica TCS SP8 X WLL2 HyVolution 2 (Leica Microsystems, Wetzlar, Germany) equipped with GaAsP (HyD) detectors and a 63Â glycerol objective (HC PL anterior-posteriorO CS2 63x/1.30 GLYC, CORR CS2). Scan speed was at 400 Hz, the pinhole was set to 0.6 Airy units, line average between 2 and 4, and the digital zoom between 1 and 2. For z-stacks, 12-bit images were captured at a slice interval of 0.24 lm with voxel size of 0.125 Â 0.125 Â 0.24 lm. Laser power or gain was adjusted for z compensation to obtain an optimal z-stack. Images were adjusted for color and contrast using Adobe Photoshop 2021 (Adobe, San Jose, CA, USA) or MorphographX (Barbier de Reuille et al., 2015) software. Image acquisition parameters for the pKAN1::KAN1:2xGFP line were the following: SR2200; 405 diode laser 0.10%, HyD 420-480 nm, detector gain 10. 2xGFP; 488 nm Argon laser 2%, HyD 525-550 nm, detector gain 100. TO-PRO-3; 642 nm White Laser 2%, HyD 660-720 nm, detector gain 100. In each case, sequential scanning was performed to avoid crosstalk between the spectra. Image acquisition parameters for the pCUC3::CFP line were the following: SR2200; 405 diode laser 0.10%, HyD 420-480 nm, detector gain 10. CFP; 514 nm Argon laser 2%, HyD 525-550 nm, detector gain 100. TO-PRO-3; 642 nm White Laser 2%, HyD 660-720 nm, detector gain 100. In each case, sequential scanning was performed to avoid crosstalk between the spectra. Imaging conditions for the Marchantia archegonia stained with SR2200 and TO-PRO-3 iodide were the same as for the ovules. In the late stage, Marchantia archegonium was imaged using the same 63 Â glycerol objective and a tilescan of 8 tiles. For z-stacks of the older specimen, 8-bit images were captured at a slice interval of 0.33 lm with voxel size of 0.126 Â 0.126 Â 0.33 lm; for z-stack of the younger 12-bit images were captured at a slice interval of 0.33 lm with voxel size of 0.127 Â 0.127 Â 0.33 lm. Tiles were stitched and merged to form the final 3D image stack of the organ in Leica Application Suite X data processing software (LASX version 3.5.7.23225). The early stage archegonium was imaged without tile scan.

Datasets and 3D instance cell segmentation
The dataset encompassing the segmented wild-type 3D digital ovules was described earlier . The two z-stacks of Marchantia archegonia were 3D cell segmented using the PlantSeg pipeline (Wolny et al., 2020). The z-stack of the Utricularia (U. gibba) trap was obtained from a fixed and modified pseudo-Schiff-stained (Truernit et al., 2008) specimen (Lee et al., 2019). 3D cell segmentation was performed using the PlantSeg-MorphoGraphX hybrid method as described in . In all instances, generation of cell surface meshes and cell type labeling was performed with MorphoGraphX. The datasets of this study have been deposited with the BioStudies data repository (https://www.ebi.ac.uk/biostudies) under the accession S-BSST734. Example dataset contains raw cell boundaries, cell boundaries, predictions from PlantSeg, nuclei images, segmented cells as well as the annotated 3D cell meshes, and the associated attribute files in csv format. The 3D meshes used in different manuscript figures are also available for download from the repository. 3D mesh files can be opened in MorphoGraphX.

Software
The MorphographX software was used for the generation of cell surface meshes, cell type labeling, and the analysis of 3D cellular features (Barbier de Reuille et al., 2015). It can be downloaded from its website (https://morphographx.org). The 3DCoordX toolbox is integrated as an add-on in MorphoGraphX version 2.0. A detailed user manual is provided in the supplement (Supplemental Text S2). The PlantSeg pipeline (Wolny et al., 2020) was used for 3D cell boundary prediction and segmentation. The software can be obtained from its Github repository (https://github.com/hciunihd/plant-seg).

Supplemental data
The following materials are available in the online version of this article.
Supplemental Figure S1. Ovule development in A. thaliana.
Supplemental Figure S2. Expression of KANADI1 in the early ovule primordium.
Supplemental Figure S3. Automatic cell layer detection in the Arabidopsis SAM.
Supplemental Figure S4. Separation of funiculus into radial and anterior and posterior domains.
Supplemental Text S1. Development of the Arabidopsis ovule.
Supplemental Text S2. User guide for annotation and analysis of complex 3D plant organsusing 3DCoordX.


Neuroprotection by Ozanimod Following Intracerebral Hemorrhage in Mice

The destruction of the blood-brain barrier (BBB) after intracerebral hemorrhage (ICH) is associated with poor prognosis. Modulation of sphingosine 1-phosphate receptor (S1PR) may improve outcomes from ICH. Ozanimod (RPC-1063) is a newly developed S1PR regulator which can selectively modulate type 1/5 sphingosine receptors. Here, we studied the impact of Ozanimod on neuroprotection in an experimental mouse model of ICH, induced by injecting collagenase type VII into the basal ganglia. Ozanimod was administered by gavage 2 h after surgery and once a day thereafter until sacrifice. The results demonstrate that Ozanimod treatment improved neurobehavioral deficits in mice and decreased weight loss after ICH. Ozanimod significantly reduced the density of activated microglia and infiltrated neutrophils in the perihematoma region. Furthermore, Ozanimod reduced hematoma volume and water content of the ICH brain. The results of TUNEL staining indicate that Ozanimod mitigated brain cell death. The quantitative data of Evans blue (EB) staining showed that Ozanimod reduced EB dye leakage. Overall, Ozanimod reduces the destruction of the BBB and exert neuroprotective roles following ICH in mice.

INTRODUCTION
Intracerebral hemorrhage (ICH) refers to primary non-traumatic hemorrhage in the brain parenchyma. It is a severe neurological disease, with high mortality and morbidity. Globally, more than 5 million ICH patients are reported each year, where approximately 3 million people die from the insult (Krishnamurthi et al., 2013). Following the onset of ICH, only 12-39% of patients regain independent living and daily functioning (Van Asch et al., 2010). Although the administration of recombinant activated factor VIIa and management of blood pressure can attenuate hematoma and improve functional outcomes (Mayer et al., 2005;Toyoda et al., 2019), effective treatments for ICH are yet to be developed (Keep et al., 2012;Chen et al., 2021;Zhang et al., 2022a).
Microglia are the resident immune cells in the central nervous system (CNS) (Lyu et al., 2021), with immune activities similar to peripheral immune cells such as neutrophils, lymphocytes, and monocytes (Zhao et al., 2017;Bai et al., 2020;Xue and Yong, 2020). Microglia are the first responders upon pathological changes to homeostasis after ICH (Sun et al., 2021). It has been established that disruption of the adhesions between endothelial cells (ECs) and degradation of the extracellular matrix causes irreversible bloodbrain barrier (BBB) disruption. The latter leads to deteriorated pathophysiological conditions including brain edema, because of extravasation of red blood cells and the infiltration of circulatory immune cells Zhang et al., 2022b). Thus, it is beneficial to reduce brain edema (Volbers et al., 2018) and restore the function of the BBB in patients with ICH. In this regard, targeting inflammation may represent a valuable approach to preserving the integrity of the BBB.
Ozanimod is a potent sphingosine 1-phosphate (S1P) 1/5 receptor agonist. In rodent studies, Ozanimod showed a neuroprotective effect on CNS diseases (Cohan et al., 2020). The selectivity of Ozanimod for S1PR1 is 27 times that for S1PR5, and the selectivity for S1PR1 is more than 10,000 times that for S1PR2, 3, and 4 (Scott et al., 2016). The S1PR1 subtype is present in cells of the nervous system, including astrocytes, oligodendrocytes, and neural progenitors, where it affects neurogenesis, cell migration, neurotransmission, and survival (Sun et al., 2016). Its expression on endothelial cells affects endothelial barrier function, and it co-regulates BBB function with its expression on astrocytes. The S1PR5 subtype is mainly expressed in oligodendrocytes of the central nervous system and mediates proliferation, differentiation, cell-cell interactions of the oligodendrocyte lineage, as well as neuroprotection (Van Doorn et al., 2012;Li et al., 2020). The high selectivity of Ozanimod for S1PR1 minimizes potential safety issues related to the activation of S1PR3 because there are many adverse events associated with SIPR3 (and other S1PR subtypes) which include hypertension, macular edema, pulmonary toxicity, and liver toxicity (Cohen and Chun, 2011;Gold et al., 2014;Cohen et al., 2016). Currently, the effects of a modulator of the S1PR1/5 have not been studied in ICH. In this study, we investigated the therapeutic benefits of an oral S1PR1/5 modulator Ozanimod in a mouse model of ICH.

MATERIALS AND METHODS
Animals 120 adult male C57BL/6J mice (8-10 weeks old) were provided by Beijing Vital River Experimental Animals Centre (Beijing, China). This study was conducted in accordance with the Animal Care Committee of Zhengzhou University. All animals were maintained in a specified pathogen-free (SPF) environment, with temperature of 25 • C, relative humidity of 55%, a light/dark cycle of 12 h, and free access to food and water.

Intracerebral Hemorrhage Models
The collagenase-induced ICH model was established as described previously (Xue et al., 2006;Liu et al., 2021). In brief, the mice were anesthetized with pentobarbital (40 mg/kg) by intraperitoneal injection. After successful anesthesia, the mice were placed on a stereotaxic instrument (RWD, Shenzhen, China). A small incision was made on the skin after shaving and alcohol cleaning, and the bregma was exposed by separating the subcutaneous tissue layer by layer to the surface of the skull. The skull plane was then adjusted to make the bregma and lambda at equal level. A round hole with a diameter of 0.6 mm was drilled into the skull, located 0.8 mm in front of the bregma and 2.0 mm on the right side of the midline, reaching the surface of the dura mater. Collagenase solution (0.075U in 0.5µL saline, VII; Sigma-Aldrich, Milwaukee, WI, United States) was infused at a rate of 0.1 µL/min using a Hamilton syringe under a depth of 3.5 mm below the surface of the skull, after which the needle was left for 10 min to prevent backflow. Subsequently, the incision was sutured and disinfected using iodophor. The sham operation group was injected with the same volume of saline into an identical intracranial location as collagenase, and the other steps were also identical to those of the ICH mice. Animals were strictly monitored until fully recovered from anesthesia.

Study Design and Drug Treatment
All animal studies were performed according to guidelines of ARRIVE (Animal Research: Reporting of in vivo Experiments) (Kilkenny et al., 2010;Percie Du Sert et al., 2020). A total of 120 adult C57BL/6 male mice (8-10 weeks) were randomly assigned into three groups: the sham group, the vehicle (ICH + DMSO) group, and the treatment (ICH + Ozanimod) group. The brains of all mice were collected at 3 days after ICH. We chose the 3-day time point because our previous studies demonstrated that brain edema, impairment of the BBB and the severity of the neurological deficit peaked on the 3rd day of ICH in mice (Xue et al., 2010). For the treatment settings, Ozanimod (Topscience, Shanghai, China) was dissolved in 0.5% dimethyl sulfoxide (DMSO) and diluted with 0.9% saline. After pre-testing with 0.3 mg/kg and 1 mg/kg Ozanimod, we learned that the optimal drug concentration was 1 mg/kg in ICH mice (Scott et al., 2016). The treatment group was given intragastric administration of Ozanimod (1mg/kg) once a day, and sham/vehicle group was treated with an equivalent amount of 0.5% DMSO once a day. Data were collected and analyzed by two blinded investigators. The flow chart of this experiment is showed in Figure 1A.

Neurological Function Tests
Corner turn test: The mice were placed in a corner made of plexiglass with an angle of 30 • . The mice spontaneously moved forward until the whiskers touched the plexiglass corner. The turning direction was recorded and all animals were observed 20 times in succession, with each interval not less than 1 min. The percentage of right turns [right/(right + left)] was calculated.
Neurological severity scores: In this experiment, the tests included body symmetry, gait, climbing, circling behavior, front limb symmetry, and compulsory circling. Each test was assigned a range of scores from zero to four, and the total score of 24 was regarded as the most serious defect.

Hematoma Volume Assessment
Mice were anesthetized deeply with pentobarbital (40 mg/kg). After perfusion, the brain was immediately taken out and fixed with 4% phosphate-buffered paraformaldehyde. The fixed brain was cut from the frontal lobe to the occipital lobe with a thickness Ozanimod improved functional results on the neurological severity scores and corner turn test (n = 6). (D) Ozanimod reduced postoperative weight loss in mice (n = 5). Data are presented as mean ± SD. * p < 0.05, * * p < 0.01, * * * p < 0.001, * * * * p < 0.0001. of 1 mm. The brain slices were arranged in order. We used Image-Pro + 5.0 software and the formula V = t (A 1 + A 2 + ··· + A n ), where V is the volume of the hematoma, t is the slice thickness, and A is the area of the hematoma to measure and calculate the volume of hematoma (cubic millimeters) (Song et al., 2003;Fang et al., 2014).

MRI Scanning and Measurements
We used small animal MRI system (MRS-4717, MR Solution company) to measure the water content of brain after ICH. The magnet type is superconducting, and the external environment does not affect the image quality. The main magnetic field strength is 4.7 T. The diameter of the magnet is 170 mm, and the highest magnetic field uniformity is 0.05 ppm/h. The cooling type is a dry magnet to avoid consumption of liquid helium, and the gradient inner diameter is 100 mm. The mice were anesthetized with 2% isoflurane during MRI, with the following parameters: (FSE, T2w; TR, 5,000 ms; TE, 51 ms; Field, 4.7 T; Flip Angle, 90 • ; Slice Thk, 0.8 mm; DFOA, 25.6 mm; Zoom, 221%). The calculation method of the volume of the lesion: Combine the lesion area of the T2 phase and multiply it by the slice thickness to obtain the total volume.

Brain Parenchymal Water Content Assessment
Brain parenchymal water content was measured on day 3 after ICH. The animals were anesthetized with pentobarbital (40 mg/kg) and then the brains were extracted quickly. After that, the brains were divided into ipsilateral, contralateral cerebral hemisphere, and the cerebellum (for internal reference). Brain samples were weighed on a precision electronic balance immediately after collection to determine wet weight. Then the weighed brain tissue was dried in the oven at 90 • C for 24 h. After drying, it was taken out and its dry weight was measured again. The water content of the brain was calculated as [(wet weight-dry weight)/wet weight] × 100%.

Immunohistochemistry Staining
The mice were anesthetized with an overdose of pentobarbital (40 mg/kg), and the heart was perfused with 0.1 mol/L PBS (pH = 7.4) containing 4% paraformaldehyde. The brain was cut into 5-µm-thick coronal sections for immunohistochemical staining. In brief, the sections were incubated with the primary antibodies overnight at 4 • C, including rabbit antimyeloperoxidase (MPO) monoclonal antibody (neutrophils marker, 1:800, Abcam, Cambridge, MA, United States), and rabbit anti-Iba1 polyclonal antibody (microglia marker, 1:200, Wako, Japan). The sections were washed with PBS (pH = 7.4) 3 times, 3 min each time. Sections were then incubated with horseradish peroxidase (HRP) combined with the secondary antibody rabbit immunoglobulin G (IgG) antibody (Servicebio, Wuhan, China) for 1 h at room temperature.

Immunofluorescent Staining
After the mice were perfused, brain tissue samples were fixed in phosphate buffered 4% paraformaldehyde at 4 • C overnight. The mouse brain was then cut into 5-µm thick coronal sections for immunofluorescent staining. Slices were incubated with primary antibodies including mouse anti-ZO-1 monoclonal antibody (1:300, Abcam, Cambridge, MA, United States) and mouse anti-Occludin monoclonal antibody (1:100, Abcam, Cambridge, MA, United States) overnight at 4 • C. Then, the sections were washed 3 times with PBS (pH = 7.4), and were incubated with a secondary antibody (Alexa Fluor 488 conjugated goat antimouse, Abcam, Cambridge, MA, United States) for 1 h at room temperature. Finally, sections were washed with PBS and stained with DAPI. All sections were visualized and photographed by using a fluorescence microscope (Olympus Co., Japan).

Immunofluorescent Double Staining (TUNEL and NeuN)
As in previous experiments (Zhang et al., 2022d), TUNEL staining was performed according to the manufacturer's instructions (Vazyme Biotech, Nanjing, China). In brief, the sections were performed with 10 µg/mL proteinase K for 15 min at 37 • C. After a 5-min wash in PBS, the labeled solution (labeled nucleotides and TdT enzyme) was incubated in the dark for 60 min at 37 • C. The slides were then incubated with rabbit anti-NeuN antibody (1:600, Abcam, Cambridge, MA, United States) overnight at 4 • C. After probing with secondary antibody (Alexa Fluor 488 conjugated goat anti-rabbit) (Abcam, Cambridge, MA, United States), the sections were counterstained with DAPI for 10 min. TUNEL and NeuN-positive cells were counted as dead neurons.

Western Blot Analysis
The mice were euthanized with pentobarbital (40 mg/kg) at 3 days after ICH, and brain samples were taken from the 1 to 1.5 mm area around the hematoma. Brain tissues were stored at -80 • C until analysis. In short, brain tissues were lysed with RIPA lysis buffer (Solarbio, Beijing, China) for 10 min, then were homogenized at 4 • C and centrifuged at 12,000 rpm for 10 min before the supernatant was collected for subsequent experiments. The supernatant was collected and the protein concentration was determined with the BCA protein assay Kit (Beyotime, China). All operations were performed on ice. Equal amounts of protein were loaded on an sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), electrophoresed, and then transferred to polyvinylidene difluoride (PVDF) membranes. The primary antibodies used in this study were rabbit anti-ZO-1 monoclonal antibody (1:5,000, Abcam, Cambridge, MA, United States) and rabbit anti-Occludin monoclonal antibody (1:1,000, Abcam, Cambridge, MA, United States). After incubating with primary antibodies, the membrane was washed with TBST 3 times for 15 min each. Then HRP-conjugated anti-rabbit secondary antibody IgG antibody (Servicebio, Wuhan, China) was applied at room temperature for 1 h. Finally, an enhanced chemiluminescence (ECL) detection kit was used for the visualization of bands. Image J was used to analyze the optical density (OD) of the signal.

Evans Blue Staining
The integrity of the BBB was evaluated by measuring the amount of exudation of Evans blue (EB). Evans blue dye (prepared with normal saline, 2% concentration, 4 ml/kg) was injected through the tail vein at 3 days after ICH in mice. After 2 h, the heart of the mouse was perfused with 0.1 mol/L phosphate buffered saline (PBS) to wash away the remaining dye in the blood vessels. The brain tissues of each group were quickly collected. The tissues immersed in 4 ml methanamide solution were placed in a water bath with a constant temperature of 55 • C for 24 h. The absorbance of the supernatant was measured with a spectrophotometer at 610 nm. The content of Evans blue present in the brain tissue was measured quantitatively according to a linear standard curve. The experimental results were expressed as the ratio of the EB content in the ipsilateral/contralateral brain.

Statistical Analysis
All data were expressed as mean ± standard deviation. All analyses were blinded. Analysis of variance and Bonferroni posthoc test were used for comparison between multiple groups. The t-test was used for analysis of 2 groups. The difference of p < 0.05 indicates statistical significance. Statistical analyses were performed using GraphPad Prism 8.0.1 software.

Ozanimod Promotes Recovery of Neurological Function and Body Weight After Intracerebral Hemorrhage
Ozanimod treatment markedly restored neurological function in the ICH model. Neurological severity scores of the Ozanimod group were significantly lower than those in the ICH + Vehicle group (Figure 1B, p < 0.01). We analyzed behavioral performance using the corner turn test, which showed that compared with the ICH + Vehicle group, the number of right turns was significantly reduced in the Ozanimod group ( Figure 1C, p < 0.001). During the experiment, we measured the weight changes of mice before and after the operation. Through statistical analysis, we found that the weight loss of mice with experimental ICH was reduced after drug intervention ( Figure 1D, p < 0.01).

Ozanimod Reduces Hematoma Volume and Brain Edema After Intracerebral Hemorrhage
The hematoma volume of ICH in experimental mice was calculated by traditional methods (Figure 2A), and it was significantly decreased in the Ozanimod group as compared with the vehicle group at 3 days post-ICH (Figure 2B, p < 0.05). The results of MRI ( Figure 2C) evaluation and wet/dry method also showed that brain edema in the Ozanimod group was significantly reduced at 3 days after ICH (Figure 2D, p < 0.01).

Ozanimod Alleviates Neuroinflammation After Intracerebral Hemorrhage
Microglia are considered to be the first responders to insults in the brain. By immunohistochemical staining (Figure 3A), we found that the number of microglia was significantly reduced in the perihematoma region in the Ozanimod group after 3 days of ICH in mice; there was also less infiltrated neutrophils (Figure 3B, p < 0.05; Figure 3C, p < 0.001). These results indicate that ozanimod treatment reduced post ICH neuroinflammation. (D) Ipsilateral brain water content (n = 6). Data are presented as mean ± SD. * p < 0.05, * * p < 0.01, * * * p < 0.001, * * * * p < 0.0001.

Ozanimod Reduces Intracerebral Hemorrhage -Induced Neuronal Death After Intracerebral Hemorrhage
The loss of neurons after ICH contributes to increased neurobehavioral scores. To evaluate neuronal death, we used TUNEL and NeuN double staining (Figure 4A), which showed that the number of dead neurons was decreased with Ozanimod treatment (Figure 4B, p < 0.01).

Ozanimod Improves Blood-Brain Barrier Integrity After Intracerebral Hemorrhage
Ozanimod contributed to the maintenance of BBB integrity by increasing the tight junction associated proteins ZO-1 and Occludin in the damaged brain tissue. By immunofluorescent staining (Figure 5A), we found that the signal intensity of ZO-1 and Occludin in the ICH + Ozanimod group was significantly higher than that in the ICH + Vehicle group (Figure 5B, p < 0.05; Figure 5C, p < 0.01). The western blot data also demonstrated that protein expressions of ZO-1 and Occludin was markedly improved after the administration of Ozanimod (Figure 6A, p < 0.05; Figure 6B, p < 0.05). In addition, EB staining was used to assess BBB disruption ( Figure 6C). We found that EB extravasation was significantly decreased after the intervention of Ozanimod (Figure 6D, p < 0.001), indicating that Ozanimod improves the integrity of BBB after ICH.

DISCUSSION
Ozanimod, a small molecule modulator of S1PR1/5, has shown efficacy in clinical trials in relapsing multiple sclerosis and ulcerative colitis (Sandborn et al., 2016;Lamb, 2020). Ozanimod was reported to exert anti-inflammatory effects in these FIGURE 4 | The effects of Ozanimod on neuronal death in mice after ICH. (A) TUNEL staining was used to mark dead cells (green). Immunofluorescence staining with NeuN was used to mark neurons (red), with the red arrow demonstrating dead neuronal cells. (B) Immunofluorescent staining and statistical results of death of neurons with Ozanimod or vehicle administration in mice for 3 days after ICH. Data are presented as mean ± SD (n = 6, Bar = 20 µm). * * p < 0.01, * * * * p < 0.0001.
trials. In the present study, Ozanimod significantly decreased inflammatory cells, protected BBB, reduced the degree of brain edema and improved neurological function in mice after ICH.
Although the mechanism underlying ozanimod mediated regulation of BBB integrity is not entirely clear, S1PR1 signaling may promote BBB integrity in the mouse brain (Yanagida et al., 2017). Also, continuous activation of S1PR1 may cause actin formation in ECs (Spindler et al., 2010), which can directly promote normal maintenance of tight junction associated protein complexes. Earlier studies have shown that specific knockdown of S1PR1 after birth induces loss of vascular endothelial growth factor (VEGF) and vascular endothelial growth factor 2 (VEGFR2) at cell junctions (Gaengel et al., 2012). Moreover, as a key regulator of neovascularization, S1PR1 plays a key role in BBB Data are presented as mean ± SD (n = 6). Bar = 20 µm. * p < 0.05, * * p < 0.01, * * * p < 0.001, * * * * p < 0.0001. development (Jung et al., 2012;Shao et al., 2015). Studies have also shown that S1PR5 regulates the tight connection of BBB in brain ECs (Van Doorn et al., 2012;Spampinato et al., 2021). Our current study indicates that ozanimod exerts protective effect on the BBB, however, further investigations are required to explore the associated molecular mechanisms.
Ozanimod has an advantage as a selective functional antagonist of S1PR1/5 subtypes in experimental ICH, with a short half-life, and less off-target effects on blood pressure and heart rate. We further found that ozanimod reduced brain edema in experimental ICH in accordance with the recently reported positive role of selective S1PR1 regulators (Sun et al., 2016;Bobinger et al., 2019). Siponimod, for example, has shown a tendency to reduce intracerebral edema. Experimental intracerebral edema is a prominent cause for the increase in neurobehavioral scores in mice (Durocher et al., 2021). (C) EB dye extravasation into tissue is apparent in coronal cross section images (Bar = 5 mm). (D) Statistical analysis of EB exudation (n = 6). Data are presented as mean ± SD. * p < 0.05, * * p < 0.01, * * * p < 0.001, * * * * p < 0.0001.
After intracerebral hemorrhage, neuronal cell death is an important driver of neurological deficits (Zhang et al., 2022c). Therefore, inhibiting neuronal cell death after intracerebral hemorrhage can help alleviate its clinical manifestations. In this study, we detected dead neurons around the bleed by labeling NeuN-positve neurons with TUNEL. Importantly, Ozanimod intervention significantly improved neuronal survival. The specific mechanism remains to be elucidated.
BBB disruption promotes transendothelial migration of neutrophils and activation of microglia, which are major steps in neuroinflammation. Inflammation is a complex immune response after injury, and neuroinflammation is one of the key factors determining the prognosis of neurological diseases. Although FTY-720, also known as Fingolimod, reduces neuroinflammation, several side effects have been reported (Shim and Wong, 2016) and it has no protective effect on BBB functions (Schuhmann et al., 2015). In contrast, Ozanimod reduced neuroinflammation (Musella et al., 2020) and maintained BBB function in experimental ICH mice. Relevant studies have also confirmed that tight junction associated protein plays a significant role in the maturation of the BBB and the recovery of neural function (Yang et al., 2021). In addition, immunosuppression and infection caused by stroke are the main causes of death in stroke patients (Shim and Wong, 2016). FTY-720 has a long half-life, which may be one of the reasons for its toxicity (Comi et al., 2010;Scott et al., 2016). Ozanimod has a significantly shorter half-life than FTY-720 and only acts on two of the five receptor subtypes that are mostly expressed on immune cells (Derfuss et al., 2020); this may avoid the adverse side effects of immune regulation.
Our study is limited by several factors. We only employed the collagenase type VII-induced ICH model; more models including the autologous blood-initiated paradigm should be included because collagenase is a kind of foreign matter that has side effects, such as inducing an inflammatory response. The result of Ozanimod protection would be more compelling if other models of ICH are used in future studies (Liddle et al., 2020). Finally, considering that the prognosis of ICH is determined by a variety of factors, drug intervention may not be sufficient on its own to improve prognosis. Therefore, further experiments are needed to investigate these issues.

CONCLUSION
We demonstrate for the first time that Ozanimod significantly enhances the integrity of the BBB in a mouse model of ICH. We also found that Ozanimod reduces neuroinflammation and improves neurobehavioral recovery following ICH in mice.

DATA AVAILABILITY STATEMENT
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

ETHICS STATEMENT
The animal study was reviewed and approved by the Ethics Committee of the Second Affiliated Hospital of Zhengzhou University.

AUTHOR CONTRIBUTIONS
FW wrote the manuscript and analyzed the data. XZ, YL, ZL, RZ, RW, YZ, and SK performed the experiments and collected the data. VY consulted and edited the manuscript. MX supervised the project. All authors discussed the results and agreed on the content of the manuscript.


s2fieldsofstudy: Biology Medicine

text:
Intra-amniotic administration of l-glutamine promotes intestinal maturation and enteroendocrine stimulation in chick embryos

Initial nutritional stimulation is a key driving force for small intestinal maturation. In chick embryos, administration of l-glutamine (Gln) into the amniotic fluid stimulates early development of the small intestinal epithelium by promoting enterocyte differentiation. In this study, we evaluated the effects of intra-amniotic administration of Gln on enterocyte morphology and function, and elucidated a potential enteroendocrine pathway through which Gln stimulates small intestinal maturation. Our results show that Gln stimulation at embryonic day 17 significantly increased enterocyte and microvilli dimensions by 10 and 20%, respectively, within 48 h. Post-hatch, enterocytes and microvilli were 20% longer in Gln-treated chicks. Correspondingly, Gln stimulation significantly upregulated mRNA expression of brush border nutrient transporters PepT-1 and SGLT-1 and tight junction proteins TJP-1 and TJP-2, before and after hatch (P < 0.05). Since GLP-2 signaling from intestinal L-cells is associated with enterocyte growth, functionality and integrity, we examined the effects of Gln stimulation on mRNA expression of key hormones and receptors within this enteroendocrine pathway and found significant increases in GLP-2R, IGF-1 and IGF-1R expression before and after hatch (P < 0.05). In conclusion, our findings link primary nutrient stimulation in the developing small intestine with enterocyte morphological and functional maturation and enteroendocrine signaling.

We therefore hypothesized that intra-amniotic administration of Gln will induce the growth of enterocytes and their apical brush border and enhance nutrient transporter and tight junction gene expression through L-cell stimulation.
To test this hypothesis, we conducted intra-amniotic administration of Gln (1% in 0.4% NaCl), and its diluent, NaCl (adjusted to 0.75% for equal osmolarity), in E17 chick embryos, as described previously 11,13,17,19 . We examined the effects of these treatments, compared to a non-administered control group, on pre-and post-hatch enterocyte maturation by measuring jejunal enterocyte and microvilli dimensions and quantifying mRNA expression of nutrient transporters PepT-1, SGLT-1 and tight junction proteins TJP-1, TJP-2 and Occludin. We then evaluated the involvement of L-cell signaling in Gln-induced enterocyte maturation, by visualizing intestinal GLP-2 immunoreactive cells and examining the expression of genes encoding PGB (Proclucagon, the GLP-2 precursor), GLP-2R, IGF-1 and IGF-1.

Results and discussion
The effects of intra-amniotic administration of 1% l-glutamine (Gln) and 0.75% NaCl (NaCl) on jejunal enterocyte morphometric maturation before and after hatch were examined by visualizing cellular outlines through immunostaining of the adherens junction molecule E-Cadherin (E-cad), combined with the microvilli marker Villin and DAPI nuclear staining (Fig. 1). Enterocyte lengths increased 4.3-fold between E17 and D7 in all groups, and significant differences were observed between groups at E19, hatch and D3 (P = 0.03, P = 0.01, P = 0.0003, respectively) (Fig. 1G). Compared to Control embryos, enterocytes of Gln-treated embryos were 10% longer at E19 and hatch (P = 0.01), while enterocytes of NaCl-treated embryos did not differ significantly ( Fig. 1A-C,G). At D3, enterocytes of both Gln and NaCl-treated chicks were significantly longer than those of Control embryos (by 14%, P = 0.01, and by 20%, P = 0.0002, respectively) ( Fig. 1D-G). By D7, enterocytes of Control chicks reached similar lengths to those of Gln and NaCl-treated chicks, which did not portray further increases in comparison to D3 (Fig. 1G). Enterocyte widths remained stable within groups at all pre-and post-hatch ages (Fig. 1G, bottom graph). Therefore, the observed increases in their lengths in the Gln group generated a more columnar epithelium at an earlier age. Since the intestinal epithelium of chicks reaches morphological maturity during the first week post-hatch 4 , we conclude that intra-amniotic administration of Gln promoted early onset of enterocyte growth, achieving maximal cellular columnarity at D3, rather than D7.
Villin immunostaining was confined was to enterocyte brush borders, and was barely detectable at pre-hatch ages. Post-hatch, Villin immunostaining was most prominent at D3 (representative images in Fig. 1D-F, bottom panel), and portrayed significant differences in signal intensities between groups (P = 0.03), with a 1.9-fold increase in the Gln group, compared to the Control group (P = 0.008) (Fig. 1H). In light of this result, we sought to visualize microvilli ultrastructure in high-resolution scanning electron microscopy (SEM) for examining the effects of Gln and NaCl stimulation on brush border development (Fig. 2). Results showed that at E19, microvilli of both NaCl and Gln-treated embryos were more perpendicularly oriented to enterocyte apical surfaces, compared to microvilli of Control embryos ( Fig. 2A-C). This indicates advanced brush border development, since pre-hatch microvilli straighten with age through rootlet elongation and terminal web connection 33 .
Microvilli lengths significantly differed between groups at E19 (P < 0.0001), hatch (P = 0.013), D3 (P = 0.019) and D7 (P < 0.0001) and microvilli widths significantly differed between treatment groups at D3 only (P = 0.0003). At E19, a 20% increase in microvilli lengths was measured Gln-treated embryos, compared to Control embryos (P < 0.0001), while microvilli lengths in NaCl-treated embryos did not differ from Control embryos (Fig. 2G). Similarly, microvilli at hatch were 14% longer in Gln-treated chicks, compared to Control chicks (P = 0.009), and no differences were found between NaCl-treated and Control chicks (Fig. 2G). At D3, brush borders in both treatment groups portrayed advanced development in comparison to Control chicks, as microvilli of NaCl-treated chicks were 13% longer (P = 0.045), and microvilli of Gln-treated chicks were 22% longer (P = 0.018), reaching peak values of 2.2 and 2.4 µm, respectively. Furthermore, microvilli widths at D3 were significantly reduced in NaCl and Gln-treated chicks (by 10%, P = 0.029 and 20%, P = 0.0003, respectively) compared to Control chicks ( Fig. 2D-G). Since microvilli organization was similar in all groups at this timepoint ( Fig. 2D-F), a reduction in their widths enables higher microvilli density.
Based on our previous findings, microvilli reach maximal lengths at D3 and significantly amplify enterocyte apical surface areas through their dimensions and densities 6 . Our current results indicate that intra-amniotic administration of Gln enhanced pre-hatch brush border developmental patterns, thus dramatically expanding enterocyte surface areas at D3. At D7, microvilli followed the same pattern reported in our previous work 6 , as their lengths decreased by 38, 32 and 44% in Control, NaCl and Gln treated chicks, respectively. However, microvilli of NaCl and Gln-treated chicks remained significantly longer (by 23%, P = 0.008 and 10%, P = 0.034, respectively) than microvilli of Control chicks at D7 (Fig. 2G). This finding indicates possible long-term increases in brush border surface areas following Gln stimulation, thus significantly contributing to enterocyte absorptive capacities.
Since our results revealed distinct morphological maturation of microvilli, we evaluated the effects of intraamniotic administration of Gln and NaCl on brush border nutrient transporter mRNA expression before and after hatch, as an indicative factor of enterocyte functionality. This was conducted by a Real-Time qPCR analysis of Peptide transporter 1 (PepT-1) and Sodium Glucose Cotransporter 1 (SGLT-1) (Fig. 3).
In the Control group, expression of both genes exhibited a dramatic 30-fold increases between pre-and posthatch ages, in accordance with previous findings [34][35][36] (Fig. 3A,B). Significant differences between groups were found for PepT-1 expression at hatch (P = 0.027) and D7 (P = 0.02), and for SGLT-1 expression at D3 and D7  www.nature.com/scientificreports/ (P = 0.048). The surge in PepT-1 expression at hatch was 54% higher in Gln-treated chicks, compared to Control chicks (P = 0.021), while expression in NaCl-treated chicks did not differ significantly from Control chicks. At D3 and D7, PepT-1 expression decreased in all groups, in accordance with previous reports 36 and did not differ between Gln-treated chicks and Control chicks at these ages. However, NaCl-treated chicks exhibited a 63% decrease in PepT-1 expression at D7, compared to Control chicks (P = 0.036) (Fig. 3A).
In contrast, SGLT-1 expression was similar in all groups at hatch. However, Gln-treated chicks exhibited significant, 50 and 57% increases in SGLT-1 expression in comparison to Control chicks at D3 and D7, respectively (P = 0.042), while expression in the NaCl group did not differ from the Control group at these timepoints. We conclude that intra-amniotic administration on Gln, but not NaCl, significantly improved the absorptive (G) Microvilli lengths and widths before and after hatch in Control, NaCl and Gln-treated embryos/chicks. Image analysis was conducted in FIJI software. Data are means ± standard error means from measurements of 10 microvilli from 5 villi tips in 3 individual embryos/chicks per group, at each timepoint. Asterisks mark significant differences compared to Control embryos/chicks at each timepoint by t-test: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. www.nature.com/scientificreports/ potential of di-and tri-peptides and glucose after hatch, corresponding to the enhancements in brush border morphometric parameters. An additional crucial factor for intestinal maturation is the epithelial barrier, generated by tight junctions, which develop and mature before and after hatch 37 . Additionally, tight junction formation is a key regulatory factor in brush border development 33,38,39 . We therefore examined the effects of intra-amniotic administration of Gln and NaCl on the expression of tight junction proteins 1 and 2 (TJP-1 and TJP-2, respectively), and the associated transmembrane protein Occludin 40 (Fig. 4).
Taken together, intra-amniotic administration of Gln enhanced intestinal developmental dynamics by promoting enterocyte growth, nutrient transporter expression and tight junction formation, thus improving posthatch nutrient absorption and intestinal integrity. These effects were restricted to the first week post-hatch, after which the small intestinal epithelium reaches maturity 4,10 .
In light of these results, we sought to determine the mechanism by which the administered Gln stimulated the developing small intestinal cells to initiate the observed effects. Various studies in mammals linked enhancements in intestinal morphology, function and integrity to GLP-2 secretion from enteroendocrine L-cells [28][29][30][31][32] , and Gln is a known stimulatory factor for this pathway [21][22][23] . We therefore hypothesized that the observed effects on enterocyte maturation were a result of Gln-mediated L-cell stimulation. To test this hypothesis, we first identified and characterized jejunal L-cells at pre-and post-hatch ages.
L-cells in mammals are most abundant in the ileum, and are distinguishable from enterocytes by their unique morphology and the presence of various secretory granules within their cytoplasm 41 . In chicken, L-cells were identified in the ileum at D7 by Glucagon-like Peptide 2 (GLP-2) immunoreactivity through fluorescence and . Expression in each treatment group and each timepoint is normalized to β-actin expression and relative to mean expression at E17 by the 2 −ΔΔCt method (further explained in "Methods"). Data are means ± standard error means from jejunal samples of 6 embryos/chicks per group at each timepoint. Asterisks indicate significant differences from Control embryos/chicks at each timepoint by t-test: *P < 0.05.  42 , and were also found with decreased abundancy along jejunum 43 . We therefore visualized L-cells within our jejunal samples at pre-and post-hatch ages by GLP-2 immunostaining. Though no L-cells were observed at E17, rare occurrences of L-cells were noted at E19 (≤ 1 per complete cross section, n = 6) (Fig. 5A). L-cells at E19 were restricted to villi bottoms and GLP-2 signal intensity was higher within the apical pole of the cell (Fig. 5A, right panel, arrowhead), outlining an oval cell structure. This is in contrast to adult ileal L-cells in chicken, which portray increased GLP-2 signal intensity within the basolateral pole, and possess a thin cytoplasmatic process extending into the intestinal lumen 42,43 . At hatch, L-cells were found at upper crypt regions (Fig. 5B) as well as along the villus epithelium (Fig. 5B′). Their morphology resembled that of L-cells at D7 in the jejunum (Fig. 5C,C′) and ileum 42,43 as well as adult mice ileal L-cells 41 .
These results reveal that the jejunal L-cell population appears between E17 and E19, when the embryo ingests its amniotic fluid 1,2,12,13 , and fully matures after hatch, when exogenous feeding begins. This indicates synchronization between the development of enteroendocrine function in the small intestine and primary nutritional stimulation in chick embryos, as has been described in mammals 44 .
In order to examine whether intra-amniotic administration of Gln and NaCl affected jejunal L-cell development, GLP-2 reactive cell abundances and staining intensities were measured in all groups at E19, hatch, D3 and D7. There were no significant differences in these parameters between groups at all examined timepoints www.nature.com/scientificreports/ (most likely due to their low abundancies, 3-5 per complete cross section, n = 6). Therefore, we proceeded to investigate the effects of Gln and NaCl administration on L-cell stimulation by examining the expression of genes encoding key components of L-cell signaling. Genes examined were Proglucagon B (PCB), which gives rise to GLP-2 through tissue-specific alternative splicing in chicken 45,46 , GLP-2 Receptor (GLP-2R), Insulin-like Growth Factor 1 (IGF-1) and IGF-1 Receptor (IGF-1R). Results revealed a tendency of increased expression of PCB at hatch and D3 in Gln-treated chicks, but this effect was not statistically significant due to high variability between individual Gln-treated chicks (Fig. 6A). Similarly, previous studies in chicken reported that fasting and refeeding did not affect intestinal PCB expression 45 . It may therefore be possible that the effects of intra-amniotic administration of Gln on GLP-2 synthesis occur at the post-translational level, or downstream. However, expression of GLP-2R differed between groups at E19 (P = 0.042) and D3 (P = 0.0159). Expression in the Gln group was higher by 75% (P = 0.072) and 62% (P = 0.006) than in the Control group at E19 and D3, respectively (Fig. 6B). Concurrently, IGF-1 expression at E19 also differed between groups (P = 0.028), due to a 47% increase in expression in Gln-treated embryos, compared to Control embryos (P = 0.041) (Fig. 6C). These results may indicate activation of ISEMFs to synthesize and secrete IGF-1 in response to GLP-2 binding. The effects of IGF-1 on enterocytes are mediated by its receptor, IGF-1R 27,28 , and its expression differed significantly between groups at E19, D3 and D7 (P = 0.022, P = 0.0148, P = 0.0415, respectively). This was due to significant increase in expression in Gln-treated, compared to Control embryos and chicks (by 86% at E19, P = 0.029), (by 88% at D3, P = 0.031) and (by 58% at D7, P = 0.01) (Fig. 6D). Expression of these genes in NaCl-treated embryos and chicks did not differ from the Control group at all ages ( Fig. 6A-D).
Taken together, these results demonstrate pre-and post-hatch upregulation of key components in L-cell paracrine hormonal signaling, in response to pre-hatch luminal Gln, thus linking the effects of Gln stimulation on enterocyte maturation with L-cell stimulation.
Though intra-amniotic administration of NaCl elicited some beneficial effects on enterocyte maturation, these effects were limited to post-hatch morphometric parameters. Since amniotic enrichment with NaCl was previously shown to promote proliferation in the small intestinal epithelium through activation of ion-dependent nutrient transporters during amniotic fluid ingestion 19 , it may be possible that NaCl promoted earlier morphological maturation of enterocytes, but did not stimulate L-cell signaling, and thus failed to enhance absorptive and barrier functions.
In conclusion, intra-amniotic administration of Gln enhanced enterocyte morphology, function and integrity during the critical first week post-hatch. These effects may be attributed to several pathways, including increased cellular energy due to Gln uptake and secretion of various intestinal hormones associated with enhanced intestinal functionality. Our results show that Gln-induced paracrine GLP-2 signaling, which has been widely associated with the effects described in this study [20][21][22]27,28 , as well as increased proliferation and differentiation found in our previous study 19 . Although direct evidence for this pathway has not been validated, we are the first to present a link between pre-hatch nutrient sensing and post-hatch enhancements in the developmental dynamics of small intestine of chicks. Figure 7 depicts the major findings in this study and a proposed mechanism of action. To date, studies of intestinal chemosensation in chicken have been limited to characterization and localization of enteroendocrine cells and their taste receptors 42,43,[47][48][49] . Further investigation of chicken L-cell characteristics and function is needed in order to shed light on the connection between intestinal nutrient sensing on absorption and satiety, as well as the gut-brain connection in chicken, which has been established in mammals 50,51 . Nevertheless, our findings demonstrate that activation of pre-hatch intestinal chemosensation and subsequent hormonal signaling is possible through intra-amniotic administration of specific nutrients, and results in improved intestinal morphology and function. We therefore provide a model for investigating the link between primary nutrient sensing and intestinal maturation, as well as an applicative method for shaping intestinal development in chicken.

Methods
Ethics declarations. All animal experiments were conducted following guidelines for the care and use of laboratory animals of the Israel Ministry of Health and in accordance with ARRIVE guidelines. All methods performed were approved by the Hebrew University Institutional Animal Care and Use Committee (IACUC), approval number: AG-17-15355-2.
Incubation and intra-amniotic nutrient administration. All animal experiments were conducted in accordance with ARRIVE guidelines and approved by the Hebrew University Institutional Animal Care and Use Committee (IACUC, license number: AG-17-15355-2). Fertile broiler eggs (Cobb 500, n = 150) were obtained from a commercial hatchery (Brown Ltd., Hod-Hasharon, Israel) and incubated in a Petersime hatcher at the Faculty of Agriculture of the Hebrew University, under standard conditions (37.8 °C, 60% relative humidity). Egg viability was examined by candling at the 14th day of incubation (E14) and unviable eggs were discarded. At E17, eggs were divided into three treatment groups of equal weights (n = 45 each) and placed at room temperature (RT). Intra-amniotic administration of was conducted as described previously 11 . Briefly, all eggs were disinfected by spraying of 75% ethanol. In two groups, a hole was punched at the wide egg pole, through which a 21-gauge, 1.25 inch needle was vertically inserted and a 0.6 ml sterile nutrient solution was injected into the amniotic fluid. Solutions consisted of 1% (wt/vol) l-glutamine (Sigma Aldrich, Rehovot, Israel) in 0.4% NaCl in the Gln group, and 0.75% NaCl in the NaCl group. Eggs of the Control group were not injected. Injected and Control eggs were sprayed again with 75% ethanol and placed in hatching trays inside the hatcher. Hatching occurred between E20 and E21 with no significant differences in hatching time and percentage between groups (mean hatchability was 94.3%). Chicks that hatched between E20.5 and E21 from all groups were marked according to their treatment group and housed together in a brooder with ad-libitum access to water and commercial starter feed (22% crude protein, 5. www.nature.com/scientificreports/ Tissue sampling. For embryonic tissue sampling, 6 embryos were randomly selected prior to intra-amniotic nutrient administration at E17, and 6 embryos were randomly selected from each treatment group at E19 (48 h post intra-amniotic nutrient administration). Post-hatch tissue sampling was conducted on 6 randomly selected chicks from each treatment group at hatch, day 3 post-hatch (D3) and D7. Embryos were euthanized by cervical dislocation and chicks were euthanized by CO 2 . The jejunum segment of their small intestines (a ≈1 cm piece from the midpoint between the duodenal loop and Meckel's diverticulum) was excised, lumen contents were flushed out with 4 °C phosphate buffered saline (PBS) and tissues were divided into three segments. The first segment was flash frozen in liquid nitrogen and stored at -80 °C for RNA extraction; the second segment was fixed in 3.7% formaldehyde in PBS at pH 7.4 (Sigma-Aldrich, Rehovot, Israel) for 24 h at RT for immunohistochemistry; the third segment was fixed in 2% glutaraldehyde and 4% formaldehyde in 0.2 M CaCo buffer at pH 7.4 (Sigma-Aldrich) for 24 h at RT for scanning electron microscopy.    47 . For all other target genes, custom primers were designed using Primer Blast (https:// www. ncbi. nlm. nih. gov/ tools/ primer-blast/) and listed in Table 1. All primers span exon-exon junctions, and were validated for exclusion of genomic DNA contamination on pooled chicken cDNA and genomic DNA samples by 1.5% agarose gel electrophoresis. Real-Time quantitative polymerase chain reaction (qPCR) was conducted in a Lightcycler® 96 instrument (Roche Diagnostic International, Zurich, Switzerland). Reactions were composed of 3.0 μL cDNA, diluted 1:25 in ultra-pure water (UPW), 1 μL of each primer (4 μM), 5 µL UPW and 10 μL Fast SYBR™ Green Master Mix (Sigma-Aldrich). A standard curve was generated for target and reference genes, assuring R 2 values of > 0.9 and primer efficiencies of 2 ± 0.1. All reactions were performed in duplicates and a non-template control was run for each primer pair. Reactions consisted of pre-incubation at 95 °C for 1 min, 40 cycles of 2-step amplification (95 °C for 10 s and 60 °C for 30 s), and a melting curve analysis (95 °C for 10 s, 65 °C for 60 s and 97 °C for 1 s) for confirming single product amplification. Expression levels were calculated using the 2 −ΔΔCt method 53 . Expression of all examined genes was normalized to β-actin, and changes in expression between groups at each timepoint were relative to mean ΔCt values at E17 for SGLT-1, PepT-1, TJP-1, TJP-2 and Occludin, and relative to mean ΔCt values in the Control group at each timepoint for PGB, GLP-2R, IGF-1, and IGF-1R. Statistical analysis. Data was analyzed using JMP Pro version 15.0 (SAS Institute, NC, US). In each analysis, equal variances were validated by Levene and Bartlett tests. Data was analyzed by one-way ANOVA at each timepoint and mean comparisons between each treatment group and the Control group were performed by t-test with significance set at P < 0.05. Graphical data are presented as means ± standard error means and significant differences are represented by asterisks: *P < 0.05, **P < 0.01, ***P < 0.001 ****P < 0.0001.  TGA AGT GTT TCG GGT TG  CTT CCA AAG ACA GCA GGA GG  171   TJP-2  NM_204918.1  TGA ACC ACC AAA GGG GAA GTT  ATT TCT CAG GAT GGG ACG CC  175   Occludin  NM_205128.1  AGC GCT ACA AGC AGG AGT TC  TCC TCT GCC ACA TCC TGG TAT  151   PCB  NM_205260.5  GTT CAA GGC AGC TGG CAA AA  ATG TGC CTT GTG AAT GAC GC  130   GLP-2R  NM_001163248.1  ATA CTT TTT GGT CTC TGC TCCAG CAG AGA TCC TTT GGC CTG TT  108   IGF-1R  NM_205032.2  ACC TTG TTG TGC TTG TCC CA  CTT CCG ATC AGG TCT GGG GA  124